Nuclei isolation of multiple brain cell types for omics interrogation

FANS Unfixed: Isolation and Proteomic Analysis of Mouse Cell Type-Specific Brain Nuclei

Epigenetic-mediated gene regulation orchestrates brain cell-type gene expression programs, and epigenetic dysregulation is a major driver of aging and disease-associated changes. Proteins that mediate gene regulation are mostly localized to the nucleus; however, nuclear-localized proteins are often underrepresented in gene expression studies and have been understudied in the context of the brain. To address this challenge, we have optimized an approach for nuclei isolation that is compatible with proteomic analysis. This was coupled to a mass spectrometry protocol for detecting proteins in low-concentration samples. We have generated nuclear proteomes for neurons, microglia, and oligodendrocytes from the mouse brain cortex and identified cell-type nuclear proteins associated with chromatin structure and organization, chromatin modifiers such as transcription factors, and RNA-binding proteins, among others. Our nuclear proteomics platform paves the way for assessing brain cell type changes in the nuclear proteome across health and disease, such as neurodevelopmental, aging, neurodegenerative, and neuroinflammatory conditions. Data are available via ProteomeXchange with the identifier PXD053515.

Gliovascular transcriptional perturbations in Alzheimer's disease reveal molecular mechanisms of blood brain barrier dysfunction

To uncover molecular changes underlying blood-brain-barrier dysfunction in Alzheimer's disease, we performed single nucleus RNA sequencing in 24 Alzheimer's disease and control brains and focused on vascular and astrocyte clusters as main cell types of blood-brain-barrier gliovascular-unit. The majority of the vascular transcriptional changes were in pericytes. Of the vascular molecular targets predicted to interact with astrocytic ligands, SMAD3, upregulated in Alzheimer's disease pericytes, has the highest number of ligands including VEGFA, downregulated in Alzheimer's disease astrocytes. We validated these findings with external datasets comprising 4,730 pericyte and 150,664 astrocyte nuclei. Blood SMAD3 levels are associated with Alzheimer's disease-related neuroimaging outcomes. We determined inverse relationships between pericytic SMAD3 and astrocytic VEGFA in human iPSC and zebrafish models. Here, we detect vast transcriptome changes in Alzheimer's disease at the gliovascular-unit, prioritize perturbed pericytic SMAD3-astrocytic VEGFA interactions, and validate these in cross-species models to provide a molecular mechanism of blood-brain-barrier disintegrity in Alzheimer's disease.

An Overview of Epigenetic Changes in the Parkinson's Disease Brain

Parkinson's disease is a progressive neurodegenerative disorder, predominantly of the motor system. Although some genetic components and cellular mechanisms of Parkinson's have been identified, much is still unknown. In recent years, emerging evidence has indicated that non-DNA-sequence variation (in particular epigenetic mechanisms) is likely to play a crucial role in the development and progression of the disease. Here, we present an up-to-date overview of epigenetic processes including DNA methylation, DNA hydroxymethylation, histone modifications and non-coding RNAs implicated in the brain of those with Parkinson's disease. We will also discuss the limitations of current epigenetic research in Parkinson's disease, the advantages of simultaneously studying genetics and epigenetics, and putative novel epigenetic therapies.

Genomic Mosaicism of the Brain: Origin, Impact, and Utility

Genomic mosaicism describes the phenomenon where some but not all cells within a tissue harbor unique genetic mutations. Traditionally, research focused on the impact of genomic mosaicism on clinical phenotype-motivated by its involvement in cancers and overgrowth syndromes. More recently, we increasingly shifted towards the plethora of neutral mosaic variants that can act as recorders of cellular lineage and environmental exposures. Here, we summarize the current state of the field of genomic mosaicism research with a special emphasis on our current understanding of this phenomenon in brain development and homeostasis. Although the field of genomic mosaicism has a rich history, technological advances in the last decade have changed our approaches and greatly improved our knowledge. We will provide current definitions and an overview of contemporary detection approaches for genomic mosaicism. Finally, we will discuss the impact and utility of genomic mosaicism.

Identification of a mosaic MTOR variant in purified neuronal DNA in a patient with focal cortical dysplasia using a novel depth electrode harvesting technique

OBJECTIVE

Recent studies have identified brain somatic variants as a cause of focal epilepsy. These studies relied on resected tissue from epilepsy surgery, which is not available in most patients. The use of trace tissue adherent to depth electrodes used for stereo electroencephalography (EEG) has been proposed as an alternative but is hampered by the low cell quality and contamination by nonbrain cells. Here, we use our improved depth electrode harvesting technique that purifies neuronal nuclei to achieve molecular diagnosis in a patient with focal cortical dysplasia (FCD).

METHODS

Depth electrode tips were collected, pooled by brain region and seizure onset zone, and nuclei were isolated and sorted using fluorescence-activated nuclei sorting (FANS). Somatic DNA was amplified from neuronal and astrocyte nuclei using primary template amplification followed by exome sequencing of neuronal DNA from the affected pool, unaffected pool, and saliva. The identified variant was validated using droplet digital polymerase chain reaction (PCR).

RESULTS

An 11-year-old male with drug-resistant genetic-structural epilepsy due to left anterior insula FCD had seizures from age 3 years. Stereo EEG confirmed seizure onset in the left anterior insula. The two anterior insula electrodes were combined as the affected pool and three frontal electrodes as the unaffected pool. FANS isolated 140 neuronal nuclei from the affected and 245 neuronal nuclei from the unaffected pool. A novel somatic missense MTOR variant (p.Leu489Met, CADD score 23.7) was identified in the affected neuronal sample. Droplet digital PCR confirmed a mosaic gradient (variant allele frequency = .78% in affected neuronal sample; variant was absent in all other samples).

SIGNIFICANCE

Our findings confirm that harvesting neuronal DNA from depth electrodes followed by molecular analysis to identify brain somatic variants is feasible. Our novel method represents a significant improvement compared to the previous method by focusing the analysis on high-quality cells of the cell type of interest.

A method for selective and efficient isolation of gray matter astrocytes from the spinal cord of adult mice

A growing body of evidence indicates intra- and inter-regional heterogeneity of astrocytes in the brain. However, because of a lack of an efficient method for isolating astrocytes from the spinal cord, little is known about how much spinal cord astrocytes are heterogeneous in adult mice. In this study, we developed a new method for isolating spinal astrocytes from adult mice using a cold-active protease from Bacillus licheniformis with an astrocyte cell surface antigen-2 (ACSA-2) antibody. Using fluorescence-activated cell sorting, isolated spinal ACSA-2+ cells were divided into two distinct populations, ACSA-2high and ACSA-2low. By analyzing the expression of cell-type marker genes, the ACSA-2high and ACSA-2low populations were identified as astrocytes and ependymal cells, respectively. Furthermore, ACSA-2high cells had mRNAs encoding genes that were abundantly expressed in the gray matter (GM) but not white matter astrocytes. By optimizing enzymatic isolation procedures, the yield of GM astrocytes also increased. Therefore, our newly established method enabled the selective and efficient isolation of GM astrocytes from the spinal cord of adult mice and may be useful for bulk- or single-cell RNA-sequencing under physiological and pathological conditions.

SPLICER: A Highly Efficient Base Editing Toolbox That Enables In Vivo Therapeutic Exon Skipping

Exon skipping technologies enable exclusion of targeted exons from mature mRNA transcripts, which has broad applications in molecular biology, medicine, and biotechnology. Existing exon skipping techniques include antisense oligonucleotides, targetable nucleases, and base editors, which, while effective for specific applications at some target exons, remain hindered by shortcomings, including transient effects for oligonucleotides, genotoxicity for nucleases and inconsistent exon skipping for base editors. To overcome these limitations, we created SPLICER, a toolbox of next-generation base editors consisting of near-PAMless Cas9 nickase variants fused to adenosine or cytosine deaminases for the simultaneous editing of splice acceptor (SA) and splice donor (SD) sequences. Synchronized SA and SD editing with SPLICER improves exon skipping, reduces aberrant outcomes, including cryptic splicing and intron retention, and enables skipping of exons refractory to single splice-site editing. To demonstrate the therapeutic potential of SPLICER, we targeted APP exon 17, which encodes the amino acid residues that are cleaved to form the Aβ plaques in Alzheimer's disease. SPLICER reduced the formation of Aβ42 peptides in vitro and enabled efficient exon skipping in a mouse model of Alzheimer's disease. Overall, SPLICER is a widely applicable and efficient toolbox for exon skipping with broad therapeutic applications.

Quantifying the proportion of different cell types in the human cortex using DNA methylation profiles

BACKGROUND

Due to interindividual variation in the cellular composition of the human cortex, it is essential that covariates that capture these differences are included in epigenome-wide association studies using bulk tissue. As experimentally derived cell counts are often unavailable, computational solutions have been adopted to estimate the proportion of different cell types using DNA methylation data. Here, we validate and profile the use of an expanded reference DNA methylation dataset incorporating two neuronal and three glial cell subtypes for quantifying the cellular composition of the human cortex.

RESULTS

We tested eight reference panels containing different combinations of neuronal- and glial cell types and characterised their performance in deconvoluting cell proportions from computationally reconstructed or empirically derived human cortex DNA methylation data. Our analyses demonstrate that while these novel brain deconvolution models produce accurate estimates of cellular proportions from profiles generated on postnatal human cortex samples, they are not appropriate for the use in prenatal cortex or cerebellum tissue samples. Applying our models to an extensive collection of empirical datasets, we show that glial cells are twice as abundant as neuronal cells in the human cortex and identify significant associations between increased Alzheimer's disease neuropathology and the proportion of specific cell types including a decrease in NeuNNeg/SOX10Neg nuclei and an increase of NeuNNeg/SOX10Pos nuclei.

CONCLUSIONS

Our novel deconvolution models produce accurate estimates for cell proportions in the human cortex. These models are available as a resource to the community enabling the control of cellular heterogeneity in epigenetic studies of brain disorders performed on bulk cortex tissue.

Challenges and opportunities to computationally deconvolve heterogeneous tissue with varying cell sizes using single-cell RNA-sequencing datasets

Deconvolution of cell mixtures in "bulk" transcriptomic samples from homogenate human tissue is important for understanding disease pathologies. However, several experimental and computational challenges impede transcriptomics-based deconvolution approaches using single-cell/nucleus RNA-seq reference atlases. Cells from the brain and blood have substantially different sizes, total mRNA, and transcriptional activities, and existing approaches may quantify total mRNA instead of cell type proportions. Further, standards are lacking for the use of cell reference atlases and integrative analyses of single-cell and spatial transcriptomics data. We discuss how to approach these key challenges with orthogonal "gold standard" datasets for evaluating deconvolution methods.

On the mechanism of tissue-selective gene delivery by lipid nanoparticles

The era of nucleic acid nanomedicine has arrived, as evidenced by Patisiran, a small interfering RNA (siRNA) encapsulated lipid nanoparticle (LNP), and mRNA-loaded LNPs used in COVID-19 vaccines. The diversity of nano-designs for delivering nucleic acid molecules tested in Phase II/III clinical trials reflects the potential of these technologies. These breakthroughs in non-viral gene delivery, including the use of LNPs, have attracted substantial interest worldwide for developing more effective drugs. A next step in this field is to target tissues other than the liver, which requires significant research efforts and material development. However, mechanistic studies in this area are lacking. This study compares two types of LNPs with different tissue-selectivity for delivering plasmid DNA (pDNA), one being liver-selective and the other spleen-selective, in an effort to understand the mechanisms responsible for differences in gene expression of delivered genes. We observed little difference in the biodistribution of these two LNPs despite the 100-1000-fold differences in gene expression. We then quantified the amount of delivered pDNA and mRNA expression in each tissue by quantitative real-time PCR (qPCR) to evaluate various intracellular processes, such as nuclear delivery, transcription and translation. The results showed a >100-fold difference in the translation step but there were little differences in amount of pDNA delivered to the nucleus or the amount of mRNA expression for the two LNP deliveries. Our findings suggest that endogenous factors affect gene expression efficiency not the extent of biodistribution.

Linking environmental risk factors with epigenetic mechanisms in Parkinson's disease

Sporadic Parkinson's disease (PD) is a progressive neurodegenerative disease, with a complex risk structure thought to be influenced by interactions between genetic variants and environmental exposures, although the full aetiology is unknown. Environmental factors, including pesticides, have been reported to increase the risk of developing the disease. Growing evidence suggests epigenetic changes are key mechanisms by which these environmental factors act upon gene regulation, in disease-relevant cell types. We present a systematic review critically appraising and summarising the current body of evidence of the relationship between epigenetic mechanisms and environmental risk factors in PD to inform future research in this area. Epigenetic studies of relevant environmental risk factors in animal and cell models have yielded promising results, however, research in humans is just emerging. While published studies in humans are currently relatively limited, the importance of the field for the elucidation of molecular mechanisms of pathogenesis opens clear and promising avenues for the future of PD research. Carefully designed epidemiological studies carried out in PD patients hold great potential to uncover disease-relevant gene regulatory mechanisms. Therefore, to advance this burgeoning field, we recommend broadening the scope of investigations to include more environmental exposures, increasing sample sizes, focusing on disease-relevant cell types, and recruiting more diverse cohorts.

SALL1 enforces microglia-specific DNA binding and function of SMADs to establish microglia identity

Spalt-like transcription factor 1 (SALL1) is a critical regulator of organogenesis and microglia identity. Here we demonstrate that disruption of a conserved microglia-specific super-enhancer interacting with the Sall1 promoter results in complete and specific loss of Sall1 expression in microglia. By determining the genomic binding sites of SALL1 and leveraging Sall1 enhancer knockout mice, we provide evidence for functional interactions between SALL1 and SMAD4 required for microglia-specific gene expression. SMAD4 binds directly to the Sall1 super-enhancer and is required for Sall1 expression, consistent with an evolutionarily conserved requirement of the TGFβ and SMAD homologs Dpp and Mad for cell-specific expression of Spalt in the Drosophila wing. Unexpectedly, SALL1 in turn promotes binding and function of SMAD4 at microglia-specific enhancers while simultaneously suppressing binding of SMAD4 to enhancers of genes that become inappropriately activated in enhancer knockout microglia, thereby enforcing microglia-specific functions of the TGFβ-SMAD signaling axis.

Neural cell isolation from adult macaques for high-throughput analyses and neurosphere cultures

The low number of neural progenitor cells (NPCs) present in the adult and aged primate brains represents a challenge for generating high-yield and viable in vitro cultures of primary brain cells. Here we report a step-by-step approach for the fast and reproducible isolation of high-yield and viable primary brain cells, including mature neurons, immature cells and NPCs, from adult and aged macaques. We describe the anesthesia, transcardial perfusion and brain tissue preparation; the subsequent microdissection of the regions of interest and their enzymatic dissociation, leading to the separation of single cells. The cell isolation steps of our protocol can also be used for routine cell culturing, in particular for NPC expansion and differentiation, suitable for studies of hippocampal neurogenesis in the adult macaque brain. The purified primary brain cells are largely free from myelin debris and erythrocytes, paving the way for multiple downstream applications in vitro and in vivo. When combined with single-cell profiling techniques, this approach allows an unbiased and comprehensive mapping of cell states in the adult and aged macaque brain, which is needed to advance our understanding of human cognitive and neurological diseases. The neural cell isolation protocol requires 4 h and a team of four to six users with expertize in primary brain cell isolation to avoid tissue hypoxia during the time-sensitive steps of the procedure.

Nuclei on the Rise: When Nuclei-Based Methods Meet Next-Generation Sequencing

In the last decade, we have witnessed an upsurge in nuclei-based studies, particularly coupled with next-generation sequencing. Such studies aim at understanding the molecular states that exist in heterogeneous cell populations by applying increasingly more affordable sequencing approaches, in addition to optimized methodologies developed to isolate and select nuclei. Although these powerful new methods promise unprecedented insights, it is important to understand and critically consider the associated challenges. Here, we provide a comprehensive overview of the rise of nuclei-based studies and elaborate on their advantages and disadvantages, with a specific focus on their utility for transcriptomic sequencing analyses. Improved designs and appropriate use of the various experimental strategies will result in acquiring biologically accurate and meaningful information.

Harnessing the potential of machine learning and artificial intelligence for dementia research

Progress in dementia research has been limited, with substantial gaps in our knowledge of targets for prevention, mechanisms for disease progression, and disease-modifying treatments. The growing availability of multimodal data sets opens possibilities for the application of machine learning and artificial intelligence (AI) to help answer key questions in the field. We provide an overview of the state of the science, highlighting current challenges and opportunities for utilisation of AI approaches to move the field forward in the areas of genetics, experimental medicine, drug discovery and trials optimisation, imaging, and prevention. Machine learning methods can enhance results of genetic studies, help determine biological effects and facilitate the identification of drug targets based on genetic and transcriptomic information. The use of unsupervised learning for understanding disease mechanisms for drug discovery is promising, while analysis of multimodal data sets to characterise and quantify disease severity and subtype are also beginning to contribute to optimisation of clinical trial recruitment. Data-driven experimental medicine is needed to analyse data across modalities and develop novel algorithms to translate insights from animal models to human disease biology. AI methods in neuroimaging outperform traditional approaches for diagnostic classification, and although challenges around validation and translation remain, there is optimism for their meaningful integration to clinical practice in the near future. AI-based models can also clarify our understanding of the causality and commonality of dementia risk factors, informing and improving risk prediction models along with the development of preventative interventions. The complexity and heterogeneity of dementia requires an alternative approach beyond traditional design and analytical approaches. Although not yet widely used in dementia research, machine learning and AI have the potential to unlock current challenges and advance precision dementia medicine.

Somatic CNV Detection by Single-Cell Whole-Genome Sequencing in Postmortem Human Brain

The evidence for a role of somatic mutations, including copy-number variants (CNVs), in neurodegeneration has increased in the last decade. However, the understanding of the types and origins of these mutations, and their exact contributions to disease onset and progression, is still in its infancy. The use of single-cell (or nuclear) whole-genome sequencing (scWGS) has emerged as a powerful tool to answer these questions. In the present chapter, we provide laboratory and bioinformatic protocols used successfully in our lab to detect megabase-scale CNVs in single cells from multiple system atrophy (MSA) human postmortem brains, using immunolabeling prior to selection of nuclei for whole-genome amplification (WGA). We also present an unpublished comparison of scWGS generated from the same control substantia nigra (SN) sample, using the latest versions of popular WGA chemistries, MDA and PicoPLEX. We have used this protocol to focus on brain cell types most relevant to synucleinopathies (dopaminergic [DA] neurons in Parkinson's disease [PD] and oligodendrocytes in MSA), but it can be applied to any tissue and/or cell type with appropriate markers.

Mechanical characterization of isolated mitochondria under conditions of oxidative stress

Mechanical properties have been proven to be a pivotal parameter to enhance our understanding of living systems. While research during the last decades focused on cells and tissues, little is known about the role of organelle mechanics in cell function. Here, mitochondria are of specific interest due to their involvement in numerous physiological and pathological processes, e.g., in the production and homeostasis of reactive oxygen species (ROS). Using real-time fluorescence and deformability cytometry, we present a microfluidic technology that is capable to determine the mechanical properties of individual mitochondria at a throughput exceeding 100 organelles per second. Our data on several thousands of viable mitochondria isolated from rat C6 glial cells yield a homogenous population with a median deformation that scales with the applied hydrodynamic stress. In two proof-of-principle studies, we investigated the impact of exogenously and endogenously produced ROS on mitochondria mechanics. Exposing C6 cells to hydrogen peroxide (H₂O₂) triggers superoxide production and leads to a reduction in mitochondria size while deformation is increased. In a second study, we focused on the knockout of tafazzin, which has been associated with impaired remodeling of the mitochondrial membrane and elevated levels of ROS. Interestingly, our results reveal the same mechanical alterations as observed after the exposure to H₂O₂, which points to a unified biophysical mechanism of how mitochondria respond to the presence of oxidative stress. In summary, we introduce high-throughput mechanical phenotyping into the field of organelle biology with potential applications for understanding sub-cellular dynamics that have not been accessible before.

Practical Considerations for Single-Cell Genomics

The single-cell revolution in the field of genomics is in full bloom, with clever new molecular biology tricks appearing regularly that allow researchers to explore new modalities or scale up their projects to millions of cells and beyond. Techniques abound to measure RNA expression, DNA alterations, protein abundance, chromatin accessibility, and more, all with single-cell resolution and often in combination. Despite such a rapidly changing technology landscape, there are several fundamental principles that are applicable to the majority of experimental workflows to help users avoid pitfalls and exploit the advantages of the chosen platform. In this overview article, we describe a variety of popular single-cell genomics technologies and address some common questions pertaining to study design, sample preparation, quality control, and sequencing strategy. As the majority of relevant publications currently revolve around single-cell RNA-seq, we will prioritize this genomics modality in our discussion. © 2022 Wiley Periodicals LLC.

Brain Cell Type-Specific Nuclear Proteomics Is Imperative to Resolve Neurodegenerative Disease Mechanisms

Neurodegenerative diseases (NDs) involve complex cellular mechanisms that are incompletely understood. Emerging findings have revealed that disruption of nuclear processes play key roles in ND pathogenesis. The nucleus is a nexus for gene regulation and cellular processes that together, may underlie pathomechanisms of NDs. Furthermore, many genetic risk factors for NDs encode proteins that are either present in the nucleus or are involved in nuclear processes (for example, RNA binding proteins, epigenetic regulators, or nuclear-cytoplasmic transport proteins). While recent advances in nuclear transcriptomics have been significant, studies of the nuclear proteome in brain have been relatively limited. We propose that a comprehensive analysis of nuclear proteomic alterations of various brain cell types in NDs may provide novel biological and therapeutic insights. This may be feasible because emerging technical advances allow isolation and investigation of intact nuclei from post-mortem frozen human brain tissue with cell type-specific and single-cell resolution. Accordingly, nuclei of various brain cell types harbor unique protein markers which can be used to isolate cell-type specific nuclei followed by down-stream proteomics by mass spectrometry. Here we review the literature providing a rationale for investigating proteomic changes occurring in nuclei in NDs and then highlight the potential for brain cell type-specific nuclear proteomics to enhance our understanding of distinct cellular mechanisms that drive ND pathogenesis.

An optimized protocol for single nuclei isolation from clinical biopsies for RNA-seq

Single nuclei RNA sequencing (snRNA-seq) has evolved as a powerful tool to study complex human diseases. Single cell resolution enables the study of novel cell types, biological processes, cell trajectories, and cell-cell signaling pathways. snRNA-seq largely relies on the dissociation of intact nuclei from human tissues. However, the study of complex tissues using small core biopsies presents many technical challenges. Here, an optimized protocol for single nuclei isolation is presented for frozen and RNAlater preserved human kidney biopsies. The described protocol is fast, low cost, and time effective due to the elimination of cell sorting and ultra-centrifugation. Samples can be processed in 90 min or less. This method is effective for obtaining normal nuclei morphology without signs of structural damage. Using snRNA-seq, 16 distinct kidney cell clusters were recovered from normal and peri-transplant acute kidney injury allograft samples, including immune cell clusters. Quality control measurements demonstrated that these optimizations eliminated cellular debris and allowed for a high yield of high-quality nuclei and RNA for library preparation and sequencing. Cellular disassociation did not induce cellular stress responses, which recapitulated transcriptional patterns associated with standardized methods of nuclei isolation. Future applications of this protocol will allow for thorough investigations of small biobank biopsies, identifying cell-specific injury pathways and driving the discovery of novel diagnostics and therapeutic targets.

Chromatin accessibility profiling by ATAC-seq

The assay for transposase-accessible chromatin using sequencing (ATAC-seq) provides a simple and scalable way to detect the unique chromatin landscape associated with a cell type and how it may be altered by perturbation or disease. ATAC-seq requires a relatively small number of input cells and does not require a priori knowledge of the epigenetic marks or transcription factors governing the dynamics of the system. Here we describe an updated and optimized protocol for ATAC-seq, called Omni-ATAC, that is applicable across a broad range of cell and tissue types. The ATAC-seq workflow has five main steps: sample preparation, transposition, library preparation, sequencing and data analysis. This protocol details the steps to generate and sequence ATAC-seq libraries, with recommendations for sample preparation and downstream bioinformatic analysis. ATAC-seq libraries for roughly 12 samples can be generated in 10 h by someone familiar with basic molecular biology, and downstream sequencing analysis can be implemented using benchmarked pipelines by someone with basic bioinformatics skills and with access to a high-performance computing environment.

Optimized Protocol for Proportionate CNS Cell Retrieval as a Versatile Platform for Cellular and Molecular Phenomapping in Aging and Neurodegeneration

Efficient purification of viable neural cells from the mature CNS has been historically challenging due to the heterogeneity of the inherent cell populations. Moreover, changes in cellular interconnections, membrane lipid and cholesterol compositions, compartment-specific biophysical properties, and intercellular space constituents demand technical adjustments for cell isolation at different stages of maturation and aging. Though such obstacles are addressed and partially overcome for embryonic premature and mature CNS tissues, procedural adaptations to an aged, progeroid, and degenerative CNS environment are underrepresented. Here, we describe a practical workflow for the acquisition and phenomapping of CNS neural cells at states of health, physiological and precocious aging, and genetically provoked neurodegeneration. Following recent, unprecedented evidence of post-mitotic cellular senescence (PoMiCS), the protocol appears suitable for such de novo characterization and phenotypic opposition to classical senescence. Technically, the protocol is rapid, efficient as for cellular yield and well preserves physiological cell proportions. It is suitable for a variety of downstream applications aiming at cell type-specific interrogations, including cell culture systems, Flow-FISH, flow cytometry/FACS, senescence studies, and retrieval of omic-scale DNA, RNA, and protein profiles. We expect suitability for transfer to other CNS targets and to a broad spectrum of engineered systems addressing aging, neurodegeneration, progeria, and senescence.

Small phenolic and indolic gut-dependent molecules in the primate central nervous system: levels vs. bioactivity

INTRODUCTION

A rapidly growing body of data documents associations between disease of the brain and small molecules generated by gut-microbiota (GMB). While such metabolites can affect brain function through a variety of mechanisms, the most direct action would be on the central nervous system (CNS) itself.

OBJECTIVE

Identify indolic and phenolic GMB-dependent small molecules that reach bioactive concentrations in primate CNS.

METHODS

We conducted a PubMed search for metabolomic studies of the primate CNS [brain tissue or cerebrospinal fluid (CSF)] and then selected for phenolic or indolic metabolites that (i) had been quantified, (ii) were GMB-dependent. For each chemical we then conducted a search for studies of bioactivity conducted in vitro in human cells of any kind or in CNS cells from the mouse or rat.

RESULTS

36 metabolites of interests were identified in primate CNS through targeted metabolomics. Quantification was available for 31/36 and in vitro bioactivity for 23/36. The reported CNS range for 8 metabolites 2-(3-hydroxyphenyl)acetic acid, 2-(4-hydroxyphenyl)acetic acid, 3-(3-hydroxyphenyl)propanoic acid, (E)-3-(3,4-dihydroxyphenyl)prop-2-enoic acid [caffeic acid], 3-hydroxybenzoic acid, 4-hydroxybenzoic acid, 2-acetamido-3-(1H-indol-3-yl)propanoic acid [N-acetyltryptophan], 1H-indol-3-yl hydrogen sulfate [indoxyl-3-sulfate] overlapped with a bioactive concentration. However, the number and quality of relevant studies of CNS neurochemistry as well as of bioactivity were highly limited. Structural isomers, multiple metabolites and potential confounders were inadequately considered.

CONCLUSION

The potential direct bioactivity of GMB-derived indolic and phenolic molecules on primate CNS remains largely unknown. The field requires additional strategies to identify and prioritize screening of the most promising small molecules that enter the CNS.

Subcellular metabolomics: Isolation, measurement, and applications

Metabolomics, a technique that profiles global small molecules in biological samples, has been a pivotal tool for disease diagnosis and mechanism research. The sample type in metabolomics covers a wide range, including a variety of body fluids, tissues, and cells. However, little attention was paid to the smaller, relatively independent partition systems in cells, namely the organelles. The organelles are specific compartments/places where diverse metabolic activities are happening in an orderly manner. Metabolic disorders of organelles were found to occur in various pathological conditions such as inherited metabolic diseases, diabetes, cancer, and neurodegenerative diseases. However, at the cellular level, the metabolic outcomes of organelles and cytoplasm are superimposed interactively, making it difficult to describe the changes in subcellular compartments. Therefore, characterizing the metabolic pool in the compartmentalized system is of great significance for understanding the role of organelles in physiological functions and diseases. So far, there are very few research articles or reviews related to subcellular metabolomics. In this review, subcellular fractionation and metabolite analysis methods, as well as the application of subcellular metabolomics in the physiological and pathological studies are systematically reviewed, as a practical reference to promote the continued advancement in subcellular metabolomics.

Reprogramming of Histone H3 Lysine Methylation During Plant Sexual Reproduction

Plants undergo extensive reprogramming of chromatin status during sexual reproduction, a process vital to cell specification and pluri- or totipotency establishment. As a crucial way to regulate chromatin organization and transcriptional activity, histone modification can be reprogrammed during sporogenesis, gametogenesis, and embryogenesis in flowering plants. In this review, we first introduce enzymes required for writing, recognizing, and removing methylation marks on lysine residues in histone H3 tails, and describe their differential expression patterns in reproductive tissues, then we summarize their functions in the reprogramming of H3 lysine methylation and the corresponding chromatin re-organization during sexual reproduction in Arabidopsis, and finally we discuss the molecular significance of histone reprogramming in maintaining the pluri- or totipotency of gametes and the zygote, and in establishing novel cell fates throughout the plant life cycle. Despite rapid achievements in understanding the molecular mechanism and function of the reprogramming of chromatin status in plant development, the research in this area still remains a challenge. Technological breakthroughs in cell-specific epigenomic profiling in the future will ultimately provide a solution for this challenge.